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The Solutions Engineer partners with customers to maximize business value from OpenAI models, providing technical expertise and guiding AI strategies.

The Technical Program Manager will lead the delivery of large-scale GPU clusters, coordinating with engineers and managing cross-functional teams to ensure timely, reliable production capacity.

The Software Engineer will build and scale Ads Manager, develop APIs and tools for campaign management, and ensure systems uphold safety and privacy standards.

The Full-Stack Engineer will build and optimize applications and interfaces for data acquisition, collaborating with various teams for effective data management and adherence to regulations.

The role involves optimizing performance across various systems in the Codex team, focusing on LLM inference, cloud infrastructure, and product layers. Responsibilities include identifying inefficiencies, building performance tooling, and collaborating on improvements to enhance system speed and cost efficiency.

As a Backend Software Engineer, you will design, build, and maintain backend services and APIs for automated knowledge systems, collaborating with cross-functional teams.

Build and operate a platform to qualify and optimize inference workloads across heterogeneous accelerators. Develop control-plane services, secure partner-side execution software, integration with compilers/runtimes, automated evaluation and optimization pipelines, artifact management, and tooling for reproducible performance and correctness. Diagnose cross-stack issues and collaborate with research, runtime, infrastructure, security, and partner teams.

Drive strategy, prioritization, and execution of CRM and adjacent platform initiatives for User Operations. Partner with engineering, revenue ops, data, and platform teams to design scalable CRM workflows, automation, integrations, and AI-native orchestration while aligning cross-functional stakeholders and operationalizing solutions in SOX/SOC2-controlled environments.

Design and build backend systems and infrastructure to ingest, index, retrieve, and serve financial data and enterprise knowledge; develop secure integrations and agentic workflows; ensure provenance, reliability, observability, and performance; collaborate with customers and cross-functional teams to move AI-native products from prototype to production.

Lead and deliver end-to-end, production-grade AI-powered enterprise workflows across ChatGPT surfaces, services, plugins, and connectors. Define technical direction, architecture, and measurable adoption goals; build core systems for identity, permissions, security, reliability, observability, and staged rollout; collaborate with cross-functional teams and customers to turn ambiguous needs into scalable products.